A flexible vision-based algorithm for a book sorting system

A flexible vision-based algorithm for a book sorting system is presented. The algorithm is based on a discrimination model that is adaptively generated for the current object classes by learning. The algorithm consists of an image normalization process, a feature element extraction process, a learning process, and a recognition process. The image normalization process extracts the contour of the object in an image, and geometrically normalizes the image. The feature extraction process converts the normalized image to the pyramidal representation, and the feature element is extracted from each resolution level. The learning process generates a discrimination model, which represents the differences between classes, based on hierarchical clustering. In the recognition process, the input images are hierarchically discriminated under the control of the decision tree. To evaluate the algorithm, a simulation system was implemented on a general-purpose computer and an image processor was developed